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Abstract
As part of the energy design synthesis method, complex dynamic building simulation database was created with IDA ICE code for all family house building configurations for a considered problem. In this paper, the annual heat energy demand output parameter is considered to serve as basis of a building energy design investigation. The sensitivity analysis performed by Morris' elementary effect method was used. As the result of the sensitivity analysis of the output parameter, the most important input parameters can be identified, that influence the buildings' energy efficiency, that can support further building designs.
Abstract
The aim of the research was to carry out the One-at-a-Time sensitivity analysis of a tree burning experiment simulation with a novel fuzzy logic-based method. It was observed that the precent of the remaining tree is sensitive to the moisture content, the crown-base diameter and the tree height. The other variables, which are maximum mass loss rate, maximum heat release rate, and maximum temperature at the top of the tree are moderately sensitive or not sensitive to the selected parameters. The presented results can be used in sensitivity studies and wildfire simulations.
Abstract
This study uses a three-layer backpropagation neural network combined with particle swarm optimization to control the foamed bitumen in cold recycling technology. The foaming process of bitumen is non-linear and depends on dynamic temperature. By developing a neural network model, this study effectively captures the complex relationships between temperature, water content, air pressure, and the expansion ratio and half-life of foamed bitumen. The integration of particle swarm optimization enhances the accuracy and convergence of the neural network model by optimizing the initial weights. This optimization process improves the model's ability to predict and control the quality of foamed bitumen accurately. It serves as a valuable tool for the rapid development of high-quality cold asphalt design.
Abstract
This study targeted to investigate a type of excavation slurry by local available material in Najaf region. On the other hand, chief practises is supported the deep sides of foundation in particular pile foundation and, drilling oil wells. The results of slurries are checking, for seven properties, which includes the viscosity (apparent plastic and funnel Marsh), yield stress, density, acidity, and gel power (10–0 min). Which are 11.7367, 8.8733, 38.1667, 11.5467 mPa·s, 1.1045 kg m−3, 10.9067, and 11.2683 mPa·s, respectively. On the basis of the results tests for the above properties, that is possible to produce a product that conforms to the specifications of American Petroleum Institute specifications, and according to the requirements of the standard ACI 336.3R-93:2006 without additives. The rheological behavior improvement is achieved through the breakdown of the bundles of palygorskite fibers that normally make up the texture of these mudstones by increasing the time and speed of the shear force as soon as increasing the concentration of clay powder.
Abstract
The paper deals with the capacitance of cylindrical two-dimensional capacitor which consists of Cartesian orthotropic dielectric material. The determination of the capacitance of capacitor with orthotropic dielectric material by a suitable coordinate transformation is reduced to the computation of capacitance of an isotropic capacitor. It is proven that the capacitance of a Cartesian orthotropic capacitor can be obtained in terms of an isotropic capacitor whose dielectric constant is the geometric mean of the dielectric constant of the orthotropic capacitor.
Abstract
Fair treatment of individuals in a scheduling task is essential. Unfairness can cause dissatisfaction among workers, faster obsolescence of work tools and underutilization of others. The literature's definitions vary, and there is no clear definition of general scheduling tasks.
This article explores fair scheduling through the lens of final exams, aiming to extend decision support system methodologies. It proposes a method based on Lipschitz mapping to measure fairness and presents a pseudo-algorithm for estimating optimal trend lines.
The model and the algorithm are demonstrated using the example of final exam schedules. In this way, two feasible solutions can be measured and compared in terms of fairness.
Abstract
Building information modeling is one of the trends in the modern construction industry. The use of 4D building information modeling in addition to 3D building information modeling improves project planning and leads to higher quality of the final product with minimal wastage of resources. In addition, 4D building information modeling allows creating visual effects that can be shown to clients before construction begins. The study describes the ways in which 4D building information modeling can be used, as well as some of the notable benefits. The level of awareness of this technology and the level of its use in construction practice are also described. The final part describes the main problems and tasks of this field and possible ways to solve them.
Abstract
The role of building orientation in decreasing energy consumption for cooling purposes was examined in this study. A radiation analysis was performed during the early stage of the architectural design process on a proposed four-story apartment building located in Cebu. The building's performance was evaluated using the Grasshopper Ladybug plugin on a 3D model developed in Rhinoceros. Results indicated that the optimal building orientation that produced the lowest total radiation was situated at 290° from the center of the building, with a recorded value of 731,356 kWh m−2. Conversely, the building orientation that resulted in the highest total radiation was recorded at 210°, with a value of 755,596 kWh m−2. The analysis results were utilized to make informed decisions about building orientation based on environmental factors and surrounding areas. The use of computational design tools in the early stages of architecture design improves the process by enabling designers to optimize building performance and identify potential design issues early, thereby avoiding costly problems.
Abstract
The Electronic Throttle Valve (ETV) is the core part of automotive engines which are recently used in control-by-wire cars. The estimation of its states and uncertainty is instructive for control applications. This study presents the design of Extended State Observer (ESO) for estimating the states and uncertainties of Electronic Throttle Valve (ETV). Two versions of ESOs have been proposed for estimation: Linear ESO (LESO) and Nonlinear ESO (NESO). The model of ETV is firstly developed and extended in state variable form such that the extended state stands for the uncertainty in system parameters. The design of both structures of ESOs are developed and a comparison study has been conducted to show the effectiveness of the proposed observers. Numerical simulation has been conducted to assess the performance of observers in estimating the states and uncertainties of ETV. The simulated results showed that both full order and reduced order models of ETV have the same transient characteristics. Moreover, the effectiveness of two versions of observers has been examined based on Root Mean Square of Error (RMSE) indicator. The results showed that the NESO has less estimation errors for both states and uncertainties than LESO.
Abstract
This study introduces the Chaotic Particle Swarm Optimization as an innovative variant of the traditional particle swarm optimization algorithm, addressing the issue of particle swarm optimization getting trapped in local minima with a low convergence characteristic during later iterations. Chaotic particle swarm optimization incorporates principles from chaos theory to enhance the swarm's exploration and exploitation capabilities. By introducing controlled chaotic behavior, particles exhibit more diverse and unpredictable movements in the search space, leading to improved global convergence and escape from local minima. The proposed method has been implemented and evaluated on benchmark problems to assess its effectiveness. The integration of chaos theory with particle swarm optimization offers promising opportunities for developing robust and efficient optimization techniques suitable for complex and dynamic problem domains in various real-world applications.
